Software framework for constructing 1D interior structure models based on planetary properties. Self-consistent thermodynamics are used for fluid, rock, and mineral phases. Sound speeds, attenuation, and electrical conductivities are computed as outputs. The main code is called from an input file containing all the planetary data.

The main repository is mirrored at https://github.com/NASA-Planetary-Science/PlanetProfile; any pull requests should be submitted to https://github.com/vancesteven/PlanetProfile. Read the software documentation at https://vancesteven.github.io/PlanetProfile.

We want to hear about your work with PlanetProfile! Please consider sending us a message alerting us to your work (svance@jpl.nasa.gov). Suggested acknowledgement in publications: "Data used in this work were generated using the open-source PlanetProfile software hosted on GitHub (https://github.com/vancesteven/PlanetProfile)."

PlanetProfile is available in Python and Matlab.

The recommended way to install is with pip. Developers: see below--do not install via pip.

1. (Recommended) Install all dependencies listed in the next section before proceeding.
2. At a terminal: python -m pip install PlanetProfile Python 3.8 or higher is required, and Python 3.11 is recommended. A later version of PlanetProfile will require Python 3.11. Pip will install dependencies, but a conda environment with the prerequisites listed below is recommended.
3. Create a directory where you'd like to store configurations and have folders for each body.
4. Navigate into the new directory.
5. At a terminal: python -m PlanetProfile.install This will copy files from their defaults to the current directory.
6. Run the software with, for example: python -m PlanetProfile.Main Europa or python -m PlanetProfile.Main path/to/PPBody.py or in a Python script with from PlanetProfile.Main import RunPPfile RunPPfile('Europa', 'PPEuropa.py')

1. Install all prerequisites below to a dedicated conda environment. Python 3.11 is required for developers. If you are not yet using Python 3.11, upgrade before installing prerequisites.
2. Clone this repository.
3. Navigate to the top-level directory of the repository.
4. At a terminal: python -m PlanetProfile.install PPinstall
5. Run the software with the command line interface (CLI) script, for example: python PlanetProfileCLI.py Europa or python PlanetProfileCLI.py path/to/PPBody.py

1. Download or clone this repository.
2. Install prerequisites below.
3. At a terminal: make install Or, add everything in the top-level directory except the PlanetProfile sub-folder to the Matlab path.
4. In Matlab, set the current directory to the top-level directory of the downloaded repository (top PlanetProfile folder).
5. Run the software with PPEuropa in the Matlab command prompt, or by opening and running one of the files located at Body/PPBody.m (e.g. Titan/PPTitan.m).

A simple list with install commands for Python is in the next section.

• SeaFreeze -- see https://github.com/Bjournaux/SeaFreeze
  • Python: Installed with pip: pip install SeaFreeze
  • Matlab: Download the repository to Thermodynamics/SeaFreeze and add the contents to the Matlab path.
• MoonMag -- see https://github.com/itsmoosh/MoonMag
  • Python only -- Installed with pip: pip install MoonMag
  • In Matlab, magnetic induction calculations are performed numerically and cannot incorporate lateral asymmetry in conducting layers.
• Gibbs Seawater toolbox of TEOS-10 -- see https://www.teos-10.org/
  • Python: Installed with conda via conda-forge: conda install -c conda-forge gsw
  • Matlab: Already packaged into the PlanetProfile repository along with the original license.
• Perple_X -- see http://www.perplex.ethz.ch/
  • For both Python and Matlab, Perple_X outputs are currently hosted as part of the installation, in Thermodynamics/Perple_X for Matlab and in PlanetProfile/Thermodynamics/EOSdata/Perple_X for Python. The files we use were generated with Perple_X v6.7.9.
• TauP/ObsPy (optional) -- see https://www.seis.sc.edu/taup/
  • Python: Installed with conda via conda-forge: conda install -c conda-forge obspy
  • Matlab: Download mMatTauP contents into Utilities/ and add-with-subfolders to the Matlab path.
• A working TeX/LaTeX distribution (such as TeXlive) is recommended for optimum plot labels. TeXlive is available at: https://tug.org/texlive/acquire-netinstall.html It can also be installed using pip.

If you had installed SeaFreeze before version v0.9.3, you will need to manually remove the prior installation because it was improperly packaged before. To do so, run the command python -m site and open the listed directory that ends in site-packages. Delete the files seafreeze.py and SeaFreeze_Gibbs.mat and any directories beginning with "SeaFreeze" (e.g. SeaFreeze.egg-info). Once these files have been removed, install the newer version of SeaFreeze with pip install SeaFreeze.

1. Python version 3.8+ must be installed, preferably via Anaconda. Required modules can be installed in Miniconda with the following command:
2. conda install numpy scipy matplotlib mpmath
3. Conda-forge modules can be installed in Anaconda or Miniconda with the following command:
4. conda install -c conda-forge gsw obspy spiceypy cmasher
5. AFTER the above modules have been installed with conda, install SeaFreeze, MoonMag, and hdf5storage with the following command:
6. pip install SeaFreeze MoonMag hdf5storage
7. Finally, install PlanetProfile as described above.

1. Download PlanetProfile repository.
2. Download SeaFreeze repository to PlanetProfile/Thermodynamics/SeaFreeze/ (NOT PlanetProfile/PlanetProfile/Thermodynamics).
3. Add SeaFreeze folder and sub-folders to Matlab path. Some magnetic field features require use of the SPICE toolkit through Mice. To install Mice:
4. Navigate to https://naif.jpl.nasa.gov/naif/toolkit_MATLAB.html
5. Follow the link for your operating system and download the .zip or .tar.Z file to PlanetProfile/Utilities/spice/
6. Unpack the archive (into PlanetProfile/Utilities/mice/)
7. Add PlanetProfile/Utilities/mice/src/mice/ and PlanetProfile/Utilities/mice/lib/ to your Matlab path.
8. Install necessary SPICE kernels by downloading them from https://naif.jpl.nasa.gov/pub/naif/generic_kernels/ and placing them in PlanetProfile/Utilities/spice/. The planetary constants kernel (PCK) and leap-seconds kernel (TLS) are saved in this repository, but the generic ephemeris kernels (SPK, .bsp files) are too large for us to save here. There is one for each planet's satellites, located at https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/satellites/. Currently in use are:
9. jup365.bsp
10. sat441.bsp
11. ura111.bsp
12. nep095.bsp

1. In the top-level directory, run the command python -c "from PlanetProfile.install import PPuninstall; PPuninstall()". All files named the same as the defaults will be deleted. If any non-default files have been added, you will be prompted whether you would like to delete them as well as the defaults. Empty folders will be deleted. Complete the uninstallation by deleting the entire directory and running the command pip uninstall PlanetProfile.

PlanetProfile is open source software. Please see the LICENSE file and read the guidelines for contrbuting in CONTRIBUTING.md if you are interested in joining the project. Also see our community guidelines in CODE_OF_CONDUCT.md.

• With the PlanetProfile 2.0 release, both Python and Matlab are available. The two branches do not have the same functionality yet with this release--some features exist in the Python version that are not yet implemented in the Matlab. A later release will align their functionality as much as possible. For now, the Python version is recommended.
• As of 2020-09-28, PlanetProfile v1.1.0 was released along with code for making calculations regarding magnetic induction. The development (main) branch of PlanetProfile is set up to generate profiles from minimal inputs. Output profiles that may be used along with the induction calculations may be found in the v1.1.0 release.
• The default settings include a recalculation of all parameters. It is recommended to recalculate all parameters whenever PlanetProfile is updated and any time a change in input parameters may affect layer thicknesses or other intermediate variables.

Some calculations in Python use parallel computing with the multiprocessing builtin module. There are sometimes cross-platform compatibility issues that crop up. By default, multiprocessing is enabled; disable it by setting Params.DO_PARALLEL = False in configPP.py.